Here is a gallery of our group’s publications, posters, and slide decks from various events and presentations.
Tags: Hearing aids (HAs), wearable computers, speech processing, field programmable gate arrays (FPGAs), electrophysiology (EEG), system-level design, open source hardware, embedded software, Internet of Things, research initiatives
Authors: Louis Pisha, Julian Warchall, Tamara Zubatiy, Sean Hamilton, Ching-Hua Lee, Ganz Chockalingam, Patrick P. Mercier, Rajesh Gupta, Bhaskar D. Rao, and Harinath Garudadri
Date Published: November 4th, 2019
Hearing loss is one of the most common conditions affecting older adults worldwide. Frequent complaints from the users of modern hearing aids include poor speech intelligibility in noisy environments and high cost, among other issues. However, the signal processing and audiological research needed to address these problems has long been hampered by proprietary development systems, underpowered embedded processors, and the difficulty of performing tests in real-world acoustical environments. To facilitate existing research in hearing healthcare and enable new investigations beyond what is currently possible, we have developed a modern, open-source hearing research platform, Open Speech Platform (OSP). This paper presents the system design of the complete OSP wearable platform, from hardware through firmware and software to user applications. The platform provides a complete suite of basic and advanced hearing aid features which can be adapted by researchers. It serves web apps directly from a hotspot on the wearable hardware, enabling users and researchers to control the system in real time. In addition, it can simultaneously acquire high-quality electroencephalography (EEG) or other electrophysiological signals closely synchronized to the audio. All of these features are provided in a wearable form factor with enough battery life for hours of operation in the field.
Tags: hearing aids, open source, digital signal processing, real-time, human study
Authors: Dhiman Sengupta, Arthur Boothroyd, Tamara Zubatiy, Cagri Yalcin, Dezhi Hong, Sean K. Hamilton, Rajesh Gupta, and Harinath Garudadri
Date Published: May 18th, 2020
Hearing aids help overcome the challenges associated with hearing loss, and thus greatly benefit and improve the lives of those living with hearing-impairment. Unfortunately, there is a lack of adoption of hearing aids among those that can benefit from hearing aids. Hearing researchers and audiologists are trying to address this problem through their research. However, the current proprietary hearing aid market makes it difficult for academic researchers to translate their findings into commercial use. In order to abridge this gap and accelerate research in hearing health care, we present the design and implementation of the Open Speech Platform (OSP), which consists of a co-design of open-source hardware and software. The hardware meets the industry standards and enables researchers to conduct experiments in the field. The software is designed with a systematic and modular approach to standardize algorithm implementation and simplify user interface development. We evaluate the performance of OSP regarding both its hardware and software, as well as demonstrate its usefulness via a self-fitting study involving human participants.
Tags: hearing aids, speech communication, electroacoustics, information technology, statistical mechanics models, signal processing, computer software, audiometers
Authors: Apurba Bose, Ziqi Gan, Dhiman Sengupta, and Harinath Garudadri
Year Published: 2019
The frequency-dependent nature of hearing loss poses many challenges for hearing aid design. In order to compensate for a hearing aid user’s unique hearing loss pattern, an input signal often needs to be separated into frequency bands, or channels, through a process called sub-band decomposition. In this paper, we present a real-time filter bank for hearing aids. Our filter bank features 10 channels uniformly distributed on the logarithmic scale, located at the standard audiometric frequencies used for the characterization and fitting of hearing aids. We obtained filters with very narrow passbands in the lower frequencies by employing multi-rate signal processing. Our filter bank offers a 9.1× reduction in complexity as compared to conventional signal processing. We implemented our filter bank on Open Speech Platform, an open-source hearing aid, and confirmed real-time operation.
Tags: hearing aids, speech communication, electroacoustics, information technology, wearable technology, linear filters, central processing unit
Authors: Mingchao Liang, Kuan-Lin Chen, Wenyu Zhang, Ching-Hua Lee, Bhaskar D. Rao, and Harinath Garudadri
Year Published: 2019
In this contribution, we present the noise management features of the Open Speech Platform (OSP) for hearing aid (HA) research. OSP includes basic HA modules (i) subband decomposition, (ii) wide dynamic range compression and (iii) adaptive feedback cancellation; a baseline single-channel speech enhancement (SE) based on Wiener filtering for noise subtraction. We extended OSP noise management to include a generalized sidelobe cancellation (GSC) beamforming between left and right channels, followed by the SE. Time is the scarcest resource, followed by central processing unit (CPU) resources in commercial HAs. With the proposed GSC + SE approach, we were both time and CPU limited. Release 2019a of OSP has 5.6 ms end-to-end latency and GSC requires an additional 5 ms, putting us above the 10 ms requirement. The wearable device of OSP has 4 cores, C0 – C3. C0 is used for all non-realtime tasks such as kernel, embedded web server, etc. and remaining cores are used for realtime tasks. Naive realization of GSC results in one or more cores not meeting the realtime constraints, resulting in audible artifacts. We present optimizations to meet time and CPU budgets; and preliminary objective and subjective results of the proposed system.
Tags: filter bank, channelizer, hearing aids, multirate processing, pure tone audiometry
Authors: Alice Sokolova, Dhiman Sengupta, Kuan-Lin Chen, Rajesh Gupta, Baris Aksanli, Fredric Harris, Harinath Garudadri
Date Published: October-November 2021
The frequency-dependent nature of hearing loss poses many challenges for hearing aid design. In order to compensate for a hearing aid user’s unique hearing loss pattern, an input signal often needs to be separated into frequency bands, or channels, through a process called sub-band decomposition. In this paper, we present a real-time filter bank for hearing aids. Our filter bank features 10 channels uniformly distributed on the logarithmic scale, located at the standard audiometric frequencies used for the characterization and fitting of hearing aids. We obtained filters with very narrow passbands in the lower frequencies by employing multi-rate signal processing. Our filter bank offers a 9.1× reduction in complexity as compared to conventional signal processing. We implemented our filter bank on Open Speech Platform, an open-source hearing aid, and confirmed real-time operation.
Authors: Vy Nguyen, Wayne Phung, Dhiman Sengupta, Martin Hunt, Varsha Rallapalli, and Harinath Garudadri
Date Published: August 2022
The EMA app allows researchers to author and administer surveys in real time. Ecological Momentary Assessment (EMA) has advantages over traditional survey approaches because it samples subjects within the field, maximizing ecological validity by minimizing recall bias and allowing researchers to collect temporal data. EMA is an open-source app that features accessible authoring options and response analysis, as well as background data collection.